We performed single nuclei and spatial transcriptomic sequencing on a cohort of solid tumor human brain metastasis specimens resected at Duke University Medical Center from 1998 to 2022. This includes 23 single nuclei specimens, 12 Visium standard specimens, and 4 Xenium specimens. These samples encompass metastases from lung cancer, breast cancer, melanoma, and sarcoma primaries. Analysis of these data revealed novel tumor-microenvironment cell-cell interactions associated with patient survival.
from sddb import Catalog
cohort = Catalog().collection("geo-gse325196")
cohort.members # the 12 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse325196")
coll.ordered_artifacts.to_dataframe() # the 12 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse325196 --dest data/Licenses: 12 NCBI GEO policy
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